Research On PHEV Intelligent Energy Management Strategy Based On Driving Energy Consumption Forecast

Energy management strategy is one of the core technologies of plug-in hybrid electric vehicle(PHEV).Its main function is to coordinate and distribute the use of electric energy and fuel energy of the vehicle,control the power output of the whole hybrid power system,so as to meet the requirements of dynamic performance and fuel economy of the vehicle.As a new energy vehicle,PHEV can be connected to the power grid for charging and has the advantages of both traditional hybrid electric vehicles and pure electric vehicles.So,with the development of intelligent connected vehicle and intelligent transportation systems,PHEV energy management strategies will be more diversified.At present,most of the PHEV energy management strategy can only realize the instantaneous or local optimization control of the vehicle on-board energy.Because it is unable to intelligently adapt to the changes of actual driving conditions and driving mileage,it is impossible to realize the global planning and optimization control of on-board energy on the whole planned driving path,which causes great loss to the energy management efficiency and fuel economy of the vehicle.Therefore,how to make PHEV vehicle energy management strategy more intelligent to improve energy management efficiency will become a key issue.This paper takes PHEV as the research object and aims to improve the fuel economy of the vehicle.It focuses on the theme that the energy management strategy of PHEV can intelligently adapt to the changes of actual driving scenarios and realize the global optimization management of on-board energy on the whole planned driving path.The details are as follows:(1)Based on the big data of human-vehicle-road-traffic system,and using artificial intelligence algorithms such as BP neural network and support vector machine,this paper establishes a two-level prediction model of driving energy consumption based on vehicle speed feature prediction.Moreover,the prediction model is respectively established for urban roads,suburb roads and freeway.The model verification results show that the prediction accuracy of the energy consumption of the entire planned path is about 95%,which can be effectively applied to the formulation of global energy management strategies.(2)In order to ensure that PHEV energy management strategy has good real-time application and optimization performance,an instantaneous optimized energy management strategy based on the ECMS(equivalent Consumption Minimization Strategy)is established,and the key problems existing in its application to PHEV are analyzed.It laid the foundation for the subsequent development of energy management strategies based on driving energy consumption prediction.(3)Based on the driving energy consumption prediction model and ECMS control strategy,a global adaptive energy management strategy with an A-ECMS(Adaptive Equivalent Consumption Minimization Strategy)as the core was developed.In the PHEV vehicle simulation model built in Matlab / Simulink environment,the designed control strategy is experimentally verified.The results show that the control strategy in this paper can adapt to changes in actual driving conditions and mileage,and has achieved an approximately global optimal control effect,and the fuel economy of the vehicle has been significantly improved.